from datetime import timedelta
from utils.operators.cluster_for_spark_sql_operator import SparkSqlOperator
# from jms.ods.tms.yl_tmsnew_tms_shipment_stop import jms_ods__yl_tmsnew_tms_shipment_stop
# from jms.ods.tms.yl_tmsnew_tms_shipment import jms_ods__yl_tmsnew_tms_shipment
# from jms.ods.tab.tab_barscan_unloading import jms_ods__tab_barscan_unloading
# from jms.ods.tab.tab_barscan_loading import jms_ods__tab_barscan_loading

from jms.dwd.tab.dwd_tab_barscan_unloading_base_dt import jms_dwd__dwd_tab_barscan_unloading_base_dt
from jms.dwd.tab.dwd_tab_barscan_loading_base_dt import jms_dwd__dwd_tab_barscan_loading_base_dt
from jms.dwd.tms.dwd_tmsnew_shipment_union_base_dt import jms_dwd__dwd_tmsnew_shipment_union_base_dt
from jms.dwd.tms.dwd_tmsnew_shipment_stop_union_base_dt import jms_dwd__dwd_tmsnew_shipment_stop_union_base_dt

# 配置所依赖的表所处的[任务名字]及[任务所在包的位置]

jms_dm__dm_tms_trunk_oper_eff_dt = SparkSqlOperator(
    task_id='jms_dm__dm_tms_trunk_oper_eff_dt',
    task_concurrency=1,
    pool_slots=4,
    master='yarn',
    execution_timeout=timedelta(minutes=50),
    email='yushuo@jtexpress.com',
    name='jms_dm__dm_tms_trunk_oper_eff_dt_{{ execution_date | date_add(1) | cst_ds }}',
    sql='jms/dm/dm_tms_trunk_oper_eff_dt/execute.hql',
    driver_memory='4G',
    driver_cores=2,
    executor_cores=2,
    executor_memory='4G',
    num_executors=10,  # spark.dynamicAllocation.enabled 为 True 时，num_executors 表示最少 Executor 数
    conf={'spark.dynamicAllocation.enabled': 'true',  # 动态资源开启
          'spark.shuffle.service.enabled': 'true',  # 动态资源 Shuffle 服务开启
          #'spark.dynamicAllocation.maxExecutors': 50,  # 动态资源最大扩容 Executor 数
          'spark.dynamicAllocation.maxExecutors': 20,  # 动态资源最大扩容 Executor 数
          'spark.dynamicAllocation.cachedExecutorIdleTimeout': 180,  # 动态资源自动释放闲置 Executor 的超时时间(s)
          'spark.sql.sources.partitionOverwriteMode': 'dynamic',  # 允许删改已存在的分区
          'spark.executor.memoryOverhead': '1G',  # 堆外内存
          'spark.sql.shuffle.partitions': 400,
          'spark.default.paralleism': 1200,
          'spark.hadoop.hive.exec.dynamic.partition.mode': 'true',
          'spark.network.timeout': 900,
          'spark.core.connection.ack.wait.timeout': 300,
          },
    # hiveconf={'hive.exec.dynamic.partition': 'true',  # 动态分区
    #           'hive.exec.dynamic.partition.mode': 'nonstrict',
    #           'hive.exec.max.dynamic.partitions': 20,  # 每天生成 20 个分区
    #           'hive.exec.max.dynamic.partitions.pernode': 20,  # 每天生成 20 个分区
    #           'hive.merge.mapredfiles':'true',
    #           'hive.merge.mapfiles':'true',
    #           'hive.merge.size.per.task': 128000000,
    #           "hive.merge.smallfiles.avgsize":128000000,
    #           },
    yarn_queue='pro',
)
# 设置依赖
jms_dm__dm_tms_trunk_oper_eff_dt << [
    jms_dwd__dwd_tab_barscan_unloading_base_dt
    , jms_dwd__dwd_tab_barscan_loading_base_dt
    , jms_dwd__dwd_tmsnew_shipment_union_base_dt
    , jms_dwd__dwd_tmsnew_shipment_stop_union_base_dt
]

